LlamaIndex
Data-focused LLM framework that specializes in connecting custom data sources, building RAG pipelines, and indexing knowledge for retrieval.
Last updated: April 26, 2026
Definition
LlamaIndex is the framework that prioritizes the data side of LLM applications. While LangChain spans models, agents, and data, LlamaIndex focuses on building production RAG: 100+ data loaders, sophisticated chunking strategies, multiple retrieval approaches (vector, keyword, knowledge graph, summary), and tools for evaluation of retrieval quality. It also supports agents (LlamaIndex Agents) but the core strength remains data ingestion and retrieval. Many production RAG systems use LlamaIndex for ingestion and retrieval and then hand off to LangGraph or a custom harness for the agent loop.
When To Use
Choose LlamaIndex for any RAG workload that needs sophisticated data ingestion (mixed sources, structured + unstructured) or retrieval evaluation. Pair with another framework for the agent loop.
Related Terms
Building with LlamaIndex?
I've shipped this pattern in real production systems. If you want a second pair of eyes on your architecture, that's what I do.